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Chapter 5

Chapter 5. More SQL: Complex Queries, Triggers, Views, and Schema Modification . Lecture # 11 July 12 ,2012. Aggregate Functions. Include COUNT, SUM, MAX, MIN, and AVG These can summarize information from multiple tuples into a single tuple

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Chapter 5

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  1. Chapter 5 More SQL: Complex Queries, Triggers, Views, and Schema Modification • Lecture # 11 July 12 ,2012

  2. Aggregate Functions • Include COUNT, SUM, MAX, MIN, and AVG • These can summarize information from multiple tuples into a single tuple • Query 15: Find the maximum salary, the minimum salary, and the average salary among all employees. Q15: SELECT MAX(SALARY) AS HIGH_SAL, MIN(SALARY) AS LOW_SAL, AVG(SALARY) AS MEAN_SAL FROM EMPLOYEE ;

  3. Aggregate Functions (cont.) • Query 16: Find the maximum salary, the minimum salary, and the average salary among employees who work for the 'Research' department. Q16: SELECT MAX(E.SALARY), MIN(E.SALARY), AVG(E.SALARY) FROM EMPLOYEE E, DEPARTMENT D WHERE E.DNO=D.DNUMBER AND D.DNAME='Research' ;

  4. Aggregate Functions (cont.) • Queries 17 and 18: Retrieve the total number of employees in the company (Q17), and the number of employees in the 'Research' department (Q18). (Note: COUNT(*) counts the number of selected records) Q17: SELECT COUNT (*) FROM EMPLOYEE ; Q18: SELECT COUNT (*) FROM EMPLOYEE AS E, DEPARTMENT AS D WHERE E.DNO=D.DNUMBER AND D.DNAME='Research’ ;

  5. Grouping (Partitioning Records into Subgroups) • In many cases, we want to apply the aggregate functions to subgroups of tuples in a relation • Each subgroup of tuples consists of the set of tuples that have the same value for the grouping attribute(s) – for example, employees who work in the same department (have the same DNO) • The aggregate functions are applied to each subgroup independently • SQL has a GROUP BY-clause for specifying the grouping attributes, which must also appear in the SELECT-clause (this is not correct)

  6. Grouping attributes • The statement before Query 24 on page 126 is incorrect. • SELECT a1,…,am, F1(b11,…), F2(b21,…), … • FROM R • WHERE … • GROUP BY g1, …, gn • Grouping attributes g1, …, gn do not necessarily need to appear in SELECT • Each ai must be one of the grouping attributes • Each Fi is an aggregate function, over a set of attributes bi1, bi2, … • Fi can be AVG, MIN, MAX, COUNT, etc • bij can be any attributes in R.

  7. Grouping (cont.) • Query 20: For each department, retrieve the department number, the number of employees in the department, and their average salary. Q20: SELECT DNO, COUNT (*), AVG (SALARY) FROM EMPLOYEE GROUP BY DNO ; • In Q20, the EMPLOYEE tuples are divided into groups- • Each group has same value for the grouping attribute DNO • The COUNT and AVG functions are applied to each such group of tuples separately (see Figure 5.1(a), next slide) • The SELECT-clause includes only the grouping attribute and the functions to be applied on each group of tuples

  8. Q24: • SELECT DNO, COUNT(*), AVG(SALARY) • FROM EMPLOYEE • GROUP DNO;

  9. Continued next page…

  10. Grouping (cont.) • A join condition can be used with grouping • Query 21: For each project, retrieve the project number, project name, and the number of employees who work on that project. Q21: SELECT P.PNUMBER, P.PNAME, COUNT (*) FROM PROJECT AS P, WORKS_ON AS W WHERE P.PNUMBER=W.PNO GROUP BY P.PNUMBER, P.PNAME ; • In this case, the grouping and aggregate functions are applied after the joining of the two relations

  11. The HAVING-clause • Sometimes we want to retrieve the values of these aggregate functions for only those groups that satisfy certain conditions • The HAVING-clause is used for specifying a selection condition on groups (rather than on individual tuples)

  12. The HAVING-Clause (cont.) • Query 26: For each project on which more than two employees work, retrieve the project number, project name, and the number of employees who work on that project (Figure 5.1(b) – next two slides). Q26: SELECT PNUMBER, PNAME, COUNT(*) FROM PROJECT, WORKS_ON WHERE PNUMBER=PNO GROUP BY PNUMBER, PNAME HAVING COUNT(*) > 2 ;

  13. Continued next page…

  14. Summary of SQL Queries • A query in SQL can consist of up to six clauses, but only the first two, SELECT and FROM, are mandatory. The clauses are specified in the following order:SELECT <attribute list>FROM <table list>[WHERE <condition>][GROUPBY <grouping attribute(s)>][HAVING <group condition>][ORDER BY <attribute list>] ;

  15. Summary of SQL Queries (cont.) • The SELECT-clause lists the attributes or functions to be retrieved • The FROM-clause specifies all relations (or aliases) needed in the query but not those needed in nested queries, as well as joined tables • The WHERE-clause specifies the conditions for selection and join of tuples from the relations specified in the FROM-clause • GROUP BY specifies grouping attributes • HAVING specifies a condition for selection of groups • ORDER BY specifies an order for displaying the query result • Conceptually, a query is evaluated by first applying the WHERE-clause, then GROUP BY and HAVING, and finally the SELECT-clause and ORDER BY

  16. Specifying General Constraints as Assertionsin SQL • General constraints: constraints that do not fit in the basic SQL constraints (primary keys, UNIQUE, foreign keys, NOT NULL – see Chapter 4) • Mechanism: CREAT ASSERTION • Components include: • a constraint name, • followed by CHECK, • followed by a condition that must be TRUE

  17. Assertions: An Example “The salary of an employee must not be greater than the salary of the manager of the department that the employee works for’’ CREAT ASSERTION SALARY_CONSTRAINT CHECK (NOT EXISTS (SELECT * FROM EMPLOYEE E, EMPLOYEE M, DEPARTMENT D WHERE E.SALARY > M.SALARY AND E.DNO=D.NUMBER AND D.MGRSSN=M.SSN)) constraint name, CHECK, condition

  18. Using General Assertions 1. Specify a query that violates the condition; include inside a NOT EXISTS clause 2. Query result must be empty; apply NOT EXISTS to it in the CHECK clause 3. If the query result is not empty, the assertion has been violated (CHECK will evaluate to FALSE)

  19. 3 places to use CHECK • attribute/tuple constraint • CREATE TABLE DEPARTMENT( • Dnumber INT, • CHECK (Dnumber > 0 AND Dnumber < 21) ); • CREATE TABLE DEPARTMENT( • … • CHECK (Dept_create_date <= Mgr_start_date) ); • domain constraint • CREATE DOMAIN D_NUM AS INTEGER • CHECK (Dnumber > 0 AND Dnumber < 21); • more complex constraint by CREATE ASSERTION

  20. SQL Triggers - Used to monitor a database and initiate action when certain events and conditions occur (see Section 26.1 for details) - Triggers are expressed in a syntax similar to assertions and include the following: Event • Such as an insert, deleted, or update operation Condition Action • To be taken when the condition is satisfied

  21. SQL Triggers: An Example A trigger to compare an employee’s salary to his/her supervisor during insert or update operations: CREATE TRIGGER INFORM_SUPERVISOR BEFORE INSERT OR UPDATE OF SALARY, SUPERVISOR_SSN ON EMPLOYEE FOR EACH ROW WHEN (NEW.SALARY> (SELECT SALARY FROM EMPLOYEE WHERE SSN=NEW.SUPERVISOR_SSN)) INFORM_SUPERVISOR (NEW.SUPERVISOR_SSN,NEW.SSN);

  22. Caution (NEW.SALARY> (SELECT SALARY FROM EMPLOYEE WHERE SSN=NEW.SUPERVISOR_SSN)) • > will be a mistake if the nested query returns more than one tuple; • It is better to use >ANY or >ALL (if that is what we intend to do)

  23. Triggers –Another Example • CREATE TRIGGER Update_Customer_Priority  ON SalesAFTER INSERT, UPDATE, DELETEAS... – Do the action here.

  24. Views in SQL - A view is a “virtual” table that is derived from other tables - Allows for limited update operations (since the table may not physically be stored) - Allows full query operations - A convenience for defining complex operations once and reusing the definition - Can also be used as a security mechanism

  25. Specification of Views SQL command: CREATE VIEW - a virtual table (view) name - a possible list of attribute names (for example, when arithmetic operations are specified or when we want the names to be different from the attributes in the base relations) - a query to specify the view contents

  26. SQL Views: An Example - Specify a virtual DEPT_INFO table to summarize departmental information - Makes it easier to query without having to specify the aggregate functions, GROUP BY, and HAVING CREATE VIEW DEPT_INFO(DNO, NO_EMPS, TOTAL_SAL) AS SELECT DNO, COUNT(*), SUM(SALARY) FROM EMPLOYEE GROUP BY DNO;

  27. Querying the View - We can specify SQL retrieval queries on a view table, same as on a base table: SELECT DNO FROM DEPT_INFO WHERE NO_OF_EMPS > 100; - Can also specify joins and other retrieval operations on the view

  28. SQL Views: Another Example - Specify a virtual WORKS_ON table (called WORKS_ON_NEW), with EMPLOYEE and PROJECT names (instead of numbers) - This makes it easier to query by names without having to specify the two join conditions CREATE VIEW WORKS_ON_NEW AS SELECT FNAME, LNAME, PNAME, HOURS FROM EMPLOYEE, PROJECT, WORKS_ON WHERE SSN=ESSN AND PNO=PNUMBER GROUP BY PNAME;

  29. Querying a View (cont.) We can specify SQL retrieval queries on a view table, same as on a base table: SELECT FNAME, LNAME FROM WORKS_ON_NEW WHERE PNAME=‘Research’; When no longer needed, a view can be dropped: DROP WORKS_ON_NEW;

  30. View Implementation - View implementation is hidden from the user - Two main techniques 1. Query modification: DBMS automatically modifies the view query into a query on the underlying base tables Disadvantage: Inefficient for views defined via complex queries • Especially if many queries are to be applied to the view within a short time period

  31. View Implementation (cont.) 2. View materialization: - Involves physically creating and keeping a temporary table that holds the view query result - Assumes that other queries on the view will follow Concerns: - Maintaining correspondence between the base tables and view when the base tables are updated Strategy: - Incremental update of the temporary view table

  32. Updating of Views - All views can be queried for retrievals, but many views cannot be updated - Update on a view on a single table without aggregate operations: If view includes key and NOT NULL attributes, view update may map to an update on the base table - Views involving joins and aggregate functions are generally not updatable unless they can be mapped to unique updates on the base tables

  33. Checking Views for Updatability - When a user intends to update a view, must add the clause WITH CHECK OPTION at the end of the CREATE VIEW statement - This allows the system to check for updatability - If view is not updatable, and error will be generated - If view is updatable, system will create a mapping strategy to process view updates

  34. Schema modification in SQL - There are two main commands for modifying schema constructs - DROP statement can remove named schema constructs, such as tables, constraints, assertions, views, and even schemas - ALTER statement can be used to change a table by adding or dropping of attributes and table constraints

  35. Example: DROP TABLE • Used to remove a relation (base table) and its definition • The relation can no longer be used in queries, updates, or any other commands since its description no longer exists • Example:DROP TABLE DEPENDENT;

  36. Example: DROP TABLE (cont.) • If the table being dropped is referenced from other tables, it cannot be dropped and an error is generated • By adding CASCADE, all references to the table are automatically removed • Example:DROP TABLE DEPENDENT CASCADE;

  37. Example: ALTER TABLE • Can be used to add or drop an attribute from a base relation • Suppose we want to remove the attribute BDATE from the EMPLOYEE table • Example:ALTER TABLE EMPLOYEE DROP BDATE ; • If the attribute is referenced from another table, an error is generated unless CASCADE is used • ALTER TABLE EMPLOYEE DROP BDATE CASCADE;

  38. Example: ALTER TABLE (cont.) • Suppose we want to add an attribute JOB • Will have NULLs (or some default) in all the tuples after command is executed; hence, NOT NULL not allowed for new JOB attribute • Example:ALTER TABLE EMPLOYEE ADD JOB VARCHAR(12); • The database users must enter values for the new attribute JOB for each EMPLOYEE tuple. • This can be done using the UPDATE command.

  39. Chapter 5 Summary • More Complex SQL Retrieval Queries • Specifying Additional Constraints and Actions in SQL • CREATE ASSERTION • CREATE TRIGGER • Views (virtual tables) in SQL • CREATE VIEW • Schema Modification in SQL • ADD, DROP statements

  40. Subqueries

  41. Subqueries • A parenthesized SELECT statement (subquery) in another SELECT statement. • FROM • WHERE

  42. Subquery in FROM • In place of a relation in the FROM clause, we can place another query, and then query its result. • use a tuple-variable to name tuples of the result. • Subquery in FROM is not mentioned in textbook, but is useful. • The SQL syntax on page 140 needs revision to include subquery in FROM SELECT FROM ( SELECT ... FROM … [WHERE …] [ GROUP BY … [HAVING …] ] [ORDER BY …] ) AS … [WHERE …] [ GROUP BY … [HAVING …]] [ORDER BY …]

  43. Example SELECT S.sid, S.name, R.semester, R.year FROM students AS S, ( SELECT * FROM register WHERE grade=‘A’ ) AS R WHERE S.sid=R.sid SELECT MAX(total) FROM ( SELECT sid, COUNT(*) as total FROM register GROUP BY sid ) AS R

  44. Subquery in WHERE • Subqueries in WHERE are also called nested queries • IN • EXISTS • > / < / = / >= / <= / < > ANY/ALL

  45. SELECT statements embedded in other statements • UNION, INTERSECT, EXCEPT Q4: (SELECT PNAME FROM PROJECT, DEPARTMENT, EMPLOYEE WHERE DNUM=DNUMBER AND MGRSSN=SSN AND LNAME='Smith') UNION (SELECT PNAME FROM PROJECT, WORKS_ON, EMPLOYEE WHERE PNUMBER=PNO AND ESSN=SSN AND LNAME='Smith')

  46. Correlated Subqueries • Subqueries in FROM must not be correlated SELECT * FROM Dependents AS D, ( SELECT * FROM Employee AS E WHERE E.SSN=D.ESSN ) AS R • Nested queries (Subqueries in WHERE) can be correlated

  47. Nested Queries can be deep SELECT PNO FROM WORKS_ON WHERE ESSN IN (SELECT SSN FROM EMPLOYEE WHERE LNAME=‘Smith’ AND DNO IN (SELECT DNUMBER FROM DEPARTMENT WHERE DNAME= ‘Research’) );

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